103 years ago, the Flexner report provided damning evidence of the sad state of the medical education system, and its implications for the quality of care provided and the lack of quality in biomedical research. Today, there is a growing consensus that our healthcare system is a poor learner and poorer performer yet relentlessly growing in expense. A major contribution to this perfect storm of underperformance is lack of quantified instrumentation of our healthcare system as a whole and a fundamental bottleneck in translating our state-of-the-art biomedical science into efficient, expert and monitored clinical decision-making. The creation of an efficient biomedical information commons where all health data for all individuals, under personal control, can be analyzed is an essential precondition to bringing knowledge to the science and practice of medicine.

Two points in this regard:

1. Biomedical Discovery—Finding the True Names of Disease We may pride ourselves on our distance from the herbalists who discovered symptomatic relief for fever, yet the most common diseases (e.g. diabetes, depression) continue to this day to be characterized symptomatically. Unlike infectious diseases where the name of the disease is its cause, the true names of most common diseases, now at pandemic prevalence, remain unknown. This ignorance is reflected in our symptomatic, phenomenological treatments for these diseases. Now, computationally bringing together the entire spectrum of data types pertaining to human physiology, we have the opportunity to study diseases at multiple levels (e.g. genomic/molecular, healthcare system, behavioral, epidemiological and social web) to precisely triangulate the location of every individual with respect to diagnosis (who are you most alike) and prognosis (who will you be most alike). By virtue of its comprehensive and integrative perspective, biomedical informatics can help us find the true names of disease and thereby treat them effectively.

2. Clinical Care—Performed As if We Were Living in the Pre-Internet Era. Why is it easier to find out what experienced shoppers worldwide have had with the latest digital camera than it is to determine what adverse events patients have had with a particular drug? Why are blood tests and X-rays repeated needlessly? Why can one replace an application on an iPhone with a mouse click yet require a team of engineers to do it for an electronic health record system? Why are the latest algorithms for detecting domestic abuse or selecting the right genetic test not at the finger tips of all clinicians in all settings? Among the multitude of answers to these questions, two answers stand out: a) There are all too many parties who have a stake in data inertia and opacity. That is, they perceive that their business or science would be impeded or made less rewarding by allowing individual data to flow frictionlessly. b) Too many of the leaders in medical care have not made information processing, which is at the core of medicine, central to their design of their healthcare delivery systems. Instead, these are seen as details to be managed by the "IT" staff. If we are going to make our data work to improve our health and medical science, the change required is as muchcultural as technical.